Recent Advances In Robotic Systems

This book brings together some recent advances and development in robotics. In 12 chapters, written by experts and researchers in respective fields, the book presents some up-to-date research ideas and findings in a wide range of robotics, including the design, modeling, control, learning, interaction, and navigation of robots. From an application perspective, the book covers UAVs, USVs, mobile robots, humanoid robots, graspers, and underwater robots. The unique text offers practical guidance to graduate students and researchers in research and applications in the field of robotics.

Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).

Medical robots are increasingly being used in the healthcare profession, particularly for surgical operations. Compared to traditional surgery techniques, robotic surgery results in smaller incisions, greater accuracy, and shortened recovery time. Medical robots can also be used to transport blood from one place to another, prepare substances in a hazardous environment, diagnose illnesses, care for patients, and more. As such, it is likely that robots will replace certain medical personnel in the future, leading to social consequences that are not yet fully understood. This book presents the latest developments in medical robotics and innovative designs of the future. It also examines current medical robotic systems and applications.

This book is an updated reference of research activities that bring together various theories, methods, and technologies of robotic systems and automation for manufacturing and related fields. The book includes articles on state-of-the-art robotic systems and automation for diverse avenues in automation such as advanced manufacturing, developments in design methodology, kinematics and dynamics analysis, performance analysis and evaluation, intelligent manufacturing, assembly, sensors, control theory and practice, human-machine interface, and so on. This book is an excellent research reference for engineers, researchers, and students that range from senior undergraduates to advanced doctoral students and professionals who are interested in robotics and automation.

Advanced robotics describes the use of sensor-based robotic devices which exploit powerful computers to achieve the high levels of functionality that begin to mimic intelligent human behaviour. The object of this book is to summarise developments in the base technologies, survey recent applications and highlight new advanced concepts which will influence future progress.

This book focuses on open issues of new intelligent control paradigms and their usage. Industry 4.0 requires new approaches in the context of secure connection, control, and maintenance of robotic systems, as well as enhancing their interaction with humans. The book presents recent advances in industrial robotics, and robotic design and modeling for various domains, and discusses the methodological foundations of the collaborative robotics concept as a breakthrough in modern industrial technologies. It also describes the implementation of multi-agent models, programs and methods that could be used in future processes for control, condition assessment, diagnostics, prognostication, and proactive maintenance. Further, the book addresses the issue of ensuring the space robotics systems and proposes reliable novel solutions. The authors also illustrate the integration of deep-learning methods and mathematical modeling based on examples of successful robotic systems in various countries, and analyze the connections between robotic modeling and design from the positions of new industrial challenges. The book is intended for practitioners and enterprise representatives, as well as scientists and Ph.D. and Master’s students pursuing research in the area of cyber-physical system development and implementation in various domains.

As a segment of the broader science of automation, robotics has achieved tremendous progress in recent decades due to the advances in supporting technologies such as computers, control systems, cameras and electronic vision, as well as micro and nanotechnology. Prototyping a design helps in determining system parameters, ranges, and in structuring an overall better system. Robotics is one of the industrial design fields in which prototyping is crucial for improved functionality. Prototyping of Robotic Systems: Applications of Design and Implementation provides a framework for conceptual, theoretical, and applied research in robotic prototyping and its applications. Covering the prototyping of various robotic systems including the complicated industrial robots, the tiny and delicate nanorobots, medical robots for disease diagnosis and treatment, as well as the simple robots for educational purposes, this book is a useful tool for those in the field of robotics prototyping and as a general reference tool for those in related fields.